alt Hacker NewsWhatever your workflow is, make sure that model and provider are replaceable. Frontier labs will keep leapfrogging each other, as they have been doing for months.
In order for the benefits of AI to be distributed, intelligence has to become a commodity.
As long as you control the skills, the learnings, and the infrastructure setup you will be fine.
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And don't tie yourself to a harness. Shun models that don't let you pick the harness (Google). Anthropic is indifferent at the moment because the OpenClaw craze is over. Vote with your wallet.
So, not using stuff like ChatGPT Dots?
Or using it in a way that's replaceable I guess, not having your entire work only ther, as your main machine.
This release is behind the most recent models so no leapfrogging here more like catching up (barely)
This is great in principle but in practice I don't have enough resources to maintain a stable normalization layer across 3+ inference providers, each with wildly different and evolving API/product roadmaps.
I could make it work if I didn't care about access to latest reasoning model capabilities, but then my customers would no longer be interested in any of this.
I tried the DIY provider agnostic harness thing and it performs like shit compared to what OAI, Anthropic and Google's engineers have created. I don't have a trillion dollar AI budget. I feel like these comments are sometimes written with the assumption that the reader does.